Design and real-time implementation of data-driven adaptive wide-area damping controller for back-to-back VSC-HVDC

This paper proposes a data-driven adaptive wide-area damping controller (D-WADC) for back-to-back VSC-HVDC to suppress the low frequency oscillation in a large-scale interconnected power system. The proposed D-WADC adopts a dual-loop control structure to make full use of the active and reactive power control of VSC-HVDC to improve the damping of the power system. A data-driven algorithm named the goal representation heuristic dynamic programming is employed to design the proposed D-WADC, which means the design procedure only requires the input and output data rather than the mathematic model of the concerned power system. Thus, the D-WADC can adapt to the change of operating condition through online weight modification. Besides, the adaptive delay compensator (ADC) is added to effectively compensate the stochastic delay involved in the wide-area feedback signal. Case studies are conducted based on the simplified model of a practical power system and the 16-machine system with a back-to-back VSC-HVDC. Both the simulation and hardware-in-loop experiment results verify that the proposed D-WADC can effectively suppress the low-frequency oscillation under a wide range of operating conditions, disturbances, and stochastic communication delays

Centralised Multimode Power Oscillation Damping Controller for Photovoltaic Plants with Communication Delay Compensation

Low-frequency oscillations are an inherent phenomena in transmission networks and renewable energy plants should be configured to damp them. Commonly, a centralised controller is used in PV plants to coordinate PV generators via communication channels. However, the communication systems of PV plants introduce delays of a stochastic nature that degrade the performance of centralised control algorithms. Therefore, controllers for oscillation damping may not operate correctly unless the communication channel characteristics are not considered and compensated. In this paper, a centralised controller is proposed for the oscillation damping that uses a PV plant with all the realistic effects of communication channels taken into consideration. The communication channels are modelled based on measurements taken in a laboratory environment. The controller is designed to damp several modes of oscillation by using the open-loop phase shift compensation. Theoretical developments were validated in a laboratory using four converters acting as two PV inverters, a battery and a STATCOM. A real-time processing platform was used to implement the centralised controller and to deploy the communication infrastructure. Experimental results show the communication channels impose severe restrictions on the performance of centralised POD controllers, highlighting the importance of their accurate modelling and consideration during the controller design stage

Stability Analysis of Networked Control in Smart Grids

A suitable networked control scheme and its stability analysis framework have been developed for controlling inherent electromechanical oscillatory dynamics observed in power systems. It is assumed that the feedback signals are obtained at locations away from the controller/actuator and transmitted over a communication network with the help of phasor measurement units (PMUs). Within the generic framework of networked control system (NCS), the evolution of power system dynamics and associated control actions through a communication network have been modeled as a hybrid system. The data delivery rate has been modeled as a stochastic process. The closed-loop stability analysis framework has considered the limiting probability of data dropout in computing the stability margin. The contribution is in quantifying allowable data-dropout limit for a specified closed loop performance. The research findings are useful in specifying the requirement of communication infrastructure and protocol for operating future smart grids

Multi-mode damping control approach for the optimal resilience of renewable-rich power systems

The integration of power-electronics-based power plants is developing significantly due to the proliferation of renewable energy sources. Although this type of power plant could positively affect society in terms of clean and sustainable energy, it also brings adverse effects, especially with the stability of the power system. The lack of inertia and different dynamic characteristics are the main issues associated with power-electronics-based power plants that could affect the oscillatory behaviour of the power system. Hence, it is important to design a comprehensive damping controller to damp oscillations due to the integration of a power-electronics-based power plant. This paper proposes a damping method for enhancing the oscillatory stability performance of power systems with high penetration of renewable energy systems. A resilient wide-area multimodal controller is proposed and used in conjunction with a battery energy storage system (BESS) to enhance the damping of critical modes. The proposed control also addresses resiliency issues associated with control signals and controllers. The optimal tuning of the control parameters for this proposed controller is challenging. Hence, the firefly algorithm was considered to be the optimisation method to design the wide-area multimodal controllers for BESS, wind, and photovoltaic (PV) systems. The performance of the proposed approach was assessed using a modified version of the Java Indonesian power system under various operating conditions. Both eigenvalue analysis and time-domain simulations are considered in the analysis. A comparison with other well-known metaheuristic methods was also carried out to show the proposed method’s efficacy. Obtained results confirmed the superior performance of the proposed approach in enhancing the small-signal stability of renewable-rich power systems. They also revealed that the proposed multimodal controller could enhance the penetration of renewable energy sources in the Javan power system by up to 50%. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

Forced oscillation detection amid communication uncertainties

This article proposes a novel technique for the detection of forced oscillation (FO) in a power system with the uncertainty in the measured signals. The impacts of communication uncertainties on measured signals are theoretically investigated based on the mathematical models developed in this article. A data recovery method is proposed and applied to reconstruct the signal under the effects of communication losses. The proposed FO detection with communication uncertainties is evaluated in the modified 14-machine Southeast Australian power system. A rigorous comparative analysis is made to validate the effectiveness of the proposed data recovery and FO detection methods

Wide Area Signals Based Damping Controllers for Multimachine Power Systems

Nowadays, electric power systems are stressed and pushed toward their stability margins due to increasing load demand and growing penetration levels of renewable energy sources such as wind and solar power. Due to insufficient damping in power systems, oscillations are likely to arise during transient and dynamic conditions. To avoid undesirable power system states such as tripping of transmission lines, generation sources, and loads, eventually leading to cascaded outages and blackouts, intelligent coordinated control of a power system and its elements, from a global and local perspective, is needed. The research performed in this dissertation is focused on intelligent analysis and coordinated control of a power system to damp oscillations and improve its stability. Wide area signals based coordinated control of power systems with and without a wind farm and energy storage systems is investigated. A data-driven method for power system identification is developed to obtain system matrices that can aid in the design of local and wide area signals based power system stabilizers. Modal analysis is performed to characterize oscillation modes using data-driven models. Data-driven models are used to identify the most appropriate wide-area signals to utilize as inputs to damping controller(s) and generator(s) to receive supplementary control. Virtual Generators (VGs) are developed using the phenomena of generator coherency to effectively and efficiently control power system oscillations. VG based Power System Stabilizers (VG-PSSs) are proposed for optimal damping of power system oscillations. Herein, speed deviation of VGs is used to generate a supplementary coordinated control signal for an identified generator(s) of maximum controllability. The parameters of a VG-PSS(s) are heuristically tuned to provide maximum system damping. To overcome fallouts and switching in coherent generator groups during transients, an adaptive inter-area oscillation damping controller is developed using the concept of artificial immune systems - innate and adaptive immunity. With increasing levels of electric vehicles (EVs) on the road, the potential of SmartParks (a large number of EVs in parking lots) for improving power system stability is investigated. Intelligent multi-functional control of SmartParks using fuzzy logic based controllers are investigated for damping power system oscillations, regulating transmission line power flows and bus voltages. In summary, a number of approaches and suggestions for improving modern power system stability have been presented in this dissertation